Chidinma Akah

Designed and delivered EO monitoring and visualization tools (Google Earth Engine, Power BI) that gave farm managers and stakeholders across multiple countries actionable climate intelligence, replacing manual, time-intensive reporting with automated satellite-driven workflows. I also worked on Python and R data pipelines in Azure Databricks, reducing processing time by over 60%, and automated Power BI reporting workflows that reduced weekly reporting time by more than 75%.

I worked with UAS data for environmental and vineyard research developing and documenting LiDAR and thermal infrared workflows. I processed LiDAR point clouds into DEMs, DSMs, CHMs and height metrics for biomass estimation and ecosystem monitoring, and produced RGB and thermal imagery orthomosaics and dense maps to investigate patterns relevant to vineyard irrigation. The workflows were adopted as benchmark processes within the research team.

Completed an MSc in Environmental Remote Sensing & Modelling with Distinction (1.4), focusing on satellite Earth Observation, spatial modelling and ecosystem analysis. Developed practical experience working with optical, LiDAR, thermal and climate data, alongside GIS and spatial analysis workflows and machine learning. My MSc thesis combined GEDI LiDAR and Sentinel-2 data to map vegetation structure across 1000 sq km of the KAZA Transfrontier Conservation Area.